All viruses infecting vertebrates interact with receptors during the process of cell infection, and also are challenged by antibodies that are either pre-existing in the host or generated shortly after infection. Both these interactions are critical to the success of the viral infection, but work in opposite directions. The long-term objectives of the proposed work are therefore to examine the interactions of those ligands with viral capsids in order to understand how differences in binding influences infection. This project is built around two specific aims: 1) Determine the effects of receptor binding properties on the infection of cells. Hypothesis: That differences in receptor interactions with the capsid influence the process of infection. Construct canine parvovirus (CPV) affinity-altered transferrin receptors and determine their effect on capsid binding and cell infectivity. 2) Select for variants of anti-capsid antibodies and examine their effects on viral infection. Hypothesis: That increased affinity of binding or the position of attachment will have different effects on infection. I will select antiviral antibodies with altered binding properties by directed evolution, and test their effects on viral receptor attachment and on cell infection. To complete the proposed aims, I will use a combination of molecular mutagenesis techniques along with protein engineering methods. Directed evolution studies are proposed, using libraries of mutated products which will be displayed on the surface of yeast cells, allowing selection of clones with altered affinities to capsids. PUBLIC HEALTH RELEVANCE: Both the relationships between viral receptor binding and infection, and between antibody neutralization and infection, are central to understanding viral infection, fitness and host range. Both interactions are complex and many details are still not well understood. By using a variety of approaches to engineer receptors and antibodies with altered affinities and specificities, I will be able to specifically examine these questions in a well understood model system.